A simulation model for use in designing robotic assembly cells

This study describes the application of the develop ed model to the scheduling of the Robotic Flexible Assembly Cells (RFACs). The present study is a continuation of the paper titled “Development of a Fuzz ySimulation Model of Scheduling Robotic Flexible Assembly Cells”. This new model for multi-objective scheduling problems in RFACs was based on combining a fuzzy-based mathematical model with simulation software tools. In this study, a hypothetical case study of RFACs is presented to demonstrate the effectiveness of the developed model and then compare the results that are obtained by the new methodology with the common scheduling rules. The simulation results show that the performance of the proposed methodology outperforms the most popular scheduling rules from previous research.

Multi-objective optimisation of dynamic scheduling in robotic flexible assembly cells via fuzzy-based Taguchi approach

Companies are increasingly being forced by market demands to increase the competitiveness of their products in regard to price, quality and delivery time. Development, both of product and production, is the key word in achieving this goal. This paper focuses on the following related subject: cost-effective design, with applications to robotic assembly cells. Against this background, a total productivity model is introduced, which allows an opinion to be formed about the performance of robotic assembly cells during the conceptual stage of the design process.

Automated 3D Model Generation and Programming of Robot Assembly Cells based on Neutral Files

Automatic layout generation of robotic production cells in a 3D manufacturing simulation environment

This paper focuses on the requirements for achieving automated diagnosis and error recovery in a robotic assembly cell, Untended robust operation is the goal which is discussed, and the use of a knowledge-base oriented diagnostic/control system to support on-line error recovery is advocated. It is proposed that error recovery attempts should be made, not only based on information gathered by system sensors, but also by using additional cell-specific knowledge pertaining to recovery strategies. Recovery attempts are to be made even in the absence of complete diagnosis, in order to gather additional information, A control structure developed to implement this approach is presented.

Traditionally, discrete parts or batch‐based manufacturing and process control have been quite distinct areas of design engineering. A robotic assembly cell and a glass manufacturing line has been seen as requiring differing design philosophies‐even down to instrumentation, sensors and control strategies that they may employ. This may change if an ambitious pan‐European project to develop sensor‐based systems produces hoped‐for results. The systems will be designed for incorporation into (almost) any industrial regime with minimal modification.

It wasn't always this complicated! In 1990, Seidle and Arri1 demonstrated how to easily adapt a conventional black oil simulation model for use in coalbed methane simulation. These days, when setting up a coalbed methane simulation model, one needs to worry about a single or multi-component gas description; depletion or enhanced coal bed methane recovery; single, dual or triple porosity; vertical, horizontal, or multi-lateral wells; coals only or a mix of coals and sands; and coalbed methane or coal mine methane? Correctly determining what to model is almost as daunting a task as the simulation work itself. All of these variations add complexity to the task and, in some cases, require specialized simulation models to adequately characterize the problem. This paper discusses how the exploitation and development of coalbed resources throughout the world is changing, and with it how our approach to reservoir simulation of the process is changing as well. The paper will provide a valuable resource to engineers and geoscientists faced with developing predictive tools to assist them in evaluating the optimum strategy to exploit these valuable resources.

Public visits to parks and protected areas continue to increase and may threaten the integrity of natural and cultural resources and the quality of the visitor experience. Scientists and managers have adopted the concept of carrying capacity to address the impacts of visitor use. In the context of outdoor recreation, the social component of carrying capacity refers to the level of visitor use that can be accommodated in parks and protected areas without diminishing the quality of the visitor experience to an unacceptable degree. This study expands and illustrates the use of computer simulation modeling as a tool for proactive monitoring and adaptive management of social carrying capacity at Arches National Park. A travel simulation model of daily visitor use throughout the Park's road and trail network and at selected attraction sites was developed, and simulations were conducted to estimate a daily social carrying capacity for Delicate Arch, an attraction site in Arches National Park, and for the Park as a whole. Further, a series of simulations were conducted to estimate the effect of a mandatory shuttle bus system on daily social carrying capacity of Delicate Arch to illustrate how computer simulation modeling can be used as a tool to facilitate adaptive management of social carrying capacity.

This book focuses on the design of Robotic Flexible Assembly Cell (RFAC) with multi-robots. Its main contribution consists of a new effective strategy for scheduling RFAC in a multi-product assembly environment, in which dynamic status and multi-objective optimization problems occur. The developed strategy, which is based on a combination of advanced solution approaches such as simulation, fuzzy logic, system modeling and the Taguchi optimization method, fills an important knowledge gap in the current literature and paves the way for future research towards the goal of employing flexible assembly systems as effectively as possible despite the complexity of their scheduling.

This study describes the application of the developed approach to the scheduling of the Robotic Flexible Assembly Cells (RFACs). The present study is a continuation of the paper titled "development of fuzzy AHP and TOPSIS approach for multi-objective scheduling problems in robotic flexible assembly cells". In this paper, a realistic case study of RFACs is presented to examined and verified the developed approach via implement three phases: problem description; application of FAHP-FTOPSIS; and analysis of the results. The analysis showed the stability of the results for FAHP-FTOPSIS and also verified the robustness and the appropriateness of the proposed approach. This study also demonstrated that the proposed approach can be successfully used in the multi-objective optimisation of dynamic scheduling in RFAC.

The concept of robotic flexible assembly cell (RFAC) has the potential to introduce significant improvements in system performance, as highlighted in Chap. 1. To achieve these improvements, the problems of RFAC at scheduling level need to be critically addressed. To date, researchers have paid little attention to handling the scheduling problems relevant to RFAC.

Development and Validation of a Laparoscopic Sacrocolpopexy Simulation Model for Surgical Training

<div class="htmlview paragraph">The main objective of this paper is to present the development of simulation models for use in the design of hydraulic pumps with pressure control. This includes both new compensator valve development as well as modification of existing pump design features. The discussion areas include a simulation model for two kinds of pressure regulating pumps, constant pressure and load sensing designs. The primary benefits of these models include a preview of performance in the early design phases of pump controls development, and the ability to reliably predict dynamic behavior and stability characteristics for pumps. The simulation models have been developed especially for investigation of how different geometric features of the components affect the dynamics of the system. This software tool will also facilitate the process of parameter sensitivity design studies.</div>

Discrete-Event Simulation Applied to Analysis of Waiting Lists. Evaluation of a Prioritization System for Cataract Surgery